Business intelligence and data warehousing software enable information from disparate parts of an enterprise to be obtained with relative ease. Great decision-making benefits are generated by business intelligence (BI). BI software integrates querying, reporting, on-line analytic processing (OLAP), data mining, and data warehousing functionality.
Such decision-making benefits are provided by BI software because they enable a user to process information from as many databases as comprises a business (or other) organization's data storage resources. Further, BI software allows analysis of needed transactions and summaries, without having to know which databases, servers, and/or other information sources from which the information underpinning such transactions and summaries were derived.
By way of background with respect to the applications to business and other enterprises, an ‘event’ represents a business event, which is a business activity, transaction, or a change in the state of a business entity, for instance, in a large business. Implicitly, events comprise a time of occurrence and an identity. Examples of events include, but are not limited to, issuing a purchase order, taking a customer service call, replenishing supplies, issuing a forecast, and posting an expense item.
A ‘context’ represents data associated with an event. Typically, contexts are data that are descriptive of the events. A context can also comprise historic summary data, which can be available in a data warehouse or operational data store (ODS). Context data may also be obtained from other systems of record. Context data provides additional information that may be required for adding meaning to an event. Context data, in so far as it can be conventionally utilized, can be evaluated to ascertain whether or not a given event should trigger a heightened state of scrutiny and observation by analysts of the business environment in which a business or other enterprise is immersed.
Modern businesses face significant and increasing needs to obtain real time access to key business events. This need, for instance, can be expressed as a requirement from a business person that indicates that the certain business metrics need to be monitored in real-time or that when certain changes in these metrics caused by various business events imply adverse conditions or an opportunity, this is cause for an ‘alert’, e.g., notation of event occurrence, and heightened monitoring of associated data thereafter.
The event, for example could be an increase in call volume into a call center, inventory falling below a certain threshold level, a drop in a demand forecast, increase in the number of returns of a certain product, or that defect rates from a test system exceeded pre-specified limits, etc. At the occurrence of such an event, the business person may want a corresponding alert to attract and guide her/his attention.
Conventional reporting and analysis software (variously called Business Intelligence, Query and reporting tools, Data warehouses etc.) (“BI software”) all provide reporting and analysis of business data. They do so by either executing queries directly against operational systems or by extracting and transforming in batches, operational data to an independent data store (sometimes called a data warehouse or data mart).
The above method by conventional reporting software results in the usage of a fixed (or static) data model from which data is analyzed. As a result of that, alert conditions cannot be detected without repeatedly running the reports on the data model, often resulting in poor performance of reports or an impact on the operational system itself, if reports are being run directly on it. In addition since the data is often extracted in batches, the resulting metrics are often from hours to days old and therefore unsuitable for real-time analytics.
Some conventional reporting products contain alerting technology, however the alerting is based on repeated processing of batch data and on a fixed data model that is inflexible to the needs of real-time analytics.
Other mechanisms, also called event management software provides for alert conditions to be detected and alerts sent, however, it similarly uses fixed data models and batch updates to the data model and suffers the associated drawbacks described above.
Without event processing capabilities, the ability to combine events with context, and powerful business rules processing capability, the ability of a business organization or a similar organization utilizing BI software to engage in real time data analysis is limited. Lacking ability to engage in real time data analysis, a business organization or a similar organization utilizing BI software has only a limited capability at best to react instantaneously to changes in its business and to the business environment in which it operates.